Enterprise Technology.
Reimagined.

Vendor lock-in is no longer a theoretical concern for Australian enterprises — it is a lived operational reality. Over the past decade, organisations that committed exclusively to a single hyperscaler have found themselves constrained by pricing power, regional availability limitations, and the risk of disruption when that provider experiences outages. The shift to multi-cloud is a direct response: by distributing workloads across Azure and AWS (and increasingly, purpose-built platforms for specific functions), organisations reclaim flexibility and reduce single points of failure. At Syncus, we consistently advise clients to evaluate cloud decisions not just on cost today but on strategic exit optionality over a five-year horizon.

Azure and AWS coexistence is no longer the exception — it is the operating model of most mature enterprise environments in Australia. The most common pattern we see is Azure serving as the primary identity, governance, and productivity platform (anchored by Entra ID and Microsoft 365), while AWS handles specific workloads where its service catalogue is superior: machine learning pipelines, data streaming, or purpose-built SaaS integrations. This is not about choosing a winner. It is about choosing the right tool for each job. The challenge is that these environments must be connected, secured, and observable in a coherent way — which requires deliberate architecture from the outset rather than organic sprawl.

Cost optimisation through intelligent workload placement is one of the highest-leverage activities available to cloud-mature organisations. Not all compute is equal: spot instances on AWS can be 80% cheaper than on-demand for fault-tolerant batch workloads, while Azure Reserved Instances offer superior pricing for predictable enterprise workloads tied to Microsoft licensing. Syncus conducts workload classification exercises with clients to identify which tier of compute (reserved, on-demand, spot, or serverless) best matches each application's availability and performance profile. The result is typically a 25–40% reduction in monthly cloud spend without compromising service levels.

Infrastructure as Code is the enabling technology that makes multi-cloud manageable. Without IaC, operating across two or more cloud environments creates an unmanageable configuration drift problem that compounds over time. Terraform, in particular, has emerged as the de facto standard for multi-cloud provisioning — its provider-agnostic model allows teams to express infrastructure intent once and deploy consistently across environments. At Syncus, all cloud engagements are delivered with Terraform modules, state management in Azure Blob or S3, and CI/CD pipelines that enforce policy-as-code through tools like Checkov. This approach transforms multi-cloud from a complexity multiplier into a strategic asset backed by repeatable, auditable infrastructure.

The gap between Maturity Level 1 and Maturity Level 2 in the ACSC Essential Eight is wider than most organisations anticipate. At ML1, controls need to be in place, but inconsistency across systems and environments is tolerated. At ML2, the expectation shifts to consistent, systematic implementation with documented processes and measurable coverage targets. In our experience assessing government and financial services clients across Australia, the most common ML1-to-ML2 failures occur in three areas: application control coverage on non-standard devices, MFA implementation gaps on legacy systems, and patch management that meets the spirit but not the letter of the 48-hour critical patching requirement.

Application control is where aspiration most frequently collides with operational reality. Organisations typically implement Microsoft Defender Application Control or AppLocker on managed endpoints but struggle with developer workstations, privileged access workstations, and operational technology endpoints that run specialist software outside the standard allowlist. Building an allowlist is straightforward; maintaining it across a dynamic environment where software versions change, new tools are onboarded, and legacy applications resist cataloguing requires dedicated process ownership. Syncus approaches application control as a continuous program, not a one-time implementation, with monthly allowlist reviews and automated alerting on block events to detect shadow IT before it becomes a security incident.

MFA implementation beyond basics is where organisations most frequently overestimate their maturity. Deploying Microsoft Authenticator for the Azure portal satisfies a narrow requirement, but ML2 expects MFA across all remote access pathways, all privileged accounts, and all internet-facing services that process sensitive data. The gaps we consistently identify include service accounts with interactive login capability that bypass MFA, VPN concentrators using only certificate-based authentication without a second factor, and legacy on-premises applications that lack modern authentication support. The remediation path for legacy applications often involves Azure AD Application Proxy with conditional access policies, which requires careful staging to avoid disrupting operations during transition.

Syncus approaches Essential Eight maturity uplift as a pragmatic, risk-prioritised program rather than a checkbox exercise. We begin every engagement with an honest gap assessment that distinguishes between controls that are genuinely implemented, controls that are partially implemented, and controls that are documented but not enforced. From there, we build a roadmap that sequences uplift activities based on risk exposure and operational impact, ensuring that the organisation makes measurable progress toward ML2 or ML3 without introducing disruption that causes business units to seek exemptions. Our goal is sustainable maturity — controls that remain in place 12 months after we leave, not just at the time of assessment.

The copilot era was characterised by AI that augmented human decision-making: a suggestion here, a draft there, a summary of a long meeting. Valuable, but fundamentally passive. The agentic era is different in kind. AI agents are software systems that receive a goal, break it into subtasks, call tools and APIs to gather information, make decisions, and take actions — often without a human in the loop until the task is complete or an exception occurs. In enterprise environments, this means workflows that previously required hours of human coordination can now be completed in minutes, with the AI agent handling orchestration, exception handling, and handoffs between systems autonomously.

The use cases gaining most traction in Australian enterprises right now are concentrated in two domains: document-intensive back-office processes and IT operations. In the first category, organisations are deploying agents that can receive a complex document (a contract, an invoice, a regulatory submission), extract structured data using Azure AI Document Intelligence, validate that data against business rules, trigger approvals via Power Automate, and update downstream systems — all without human touch. In IT operations, agents are being used for Level 1 triage: ingesting alerts from SIEM systems, querying configuration management databases, running diagnostic scripts, and either resolving or escalating with a full contextual summary. The throughput gains are significant; more importantly, the consistency gains are transformational.

The security and governance challenges of agentic AI are real and should not be minimised. An AI agent that can call APIs, write to databases, and send emails has a blast radius that a passive copilot does not. The key risk vectors are prompt injection (where a malicious input in a document tricks the agent into taking unintended actions), privilege escalation (where an agent is granted more access than any individual human would have), and audit trail fragmentation (where actions taken by the agent are difficult to attribute and review). Syncus addresses these through a structured governance framework: agents operate under a dedicated service identity with least-privilege access, all tool calls are logged to an immutable audit trail in Azure Monitor, and human-in-the-loop checkpoints are enforced for any action above a defined risk threshold.

Syncus deploys agentic AI solutions using the Azure AI Foundry platform, integrating with clients' existing Microsoft 365 and Azure environments to minimise integration complexity and data residency concerns. Our approach is to start with a bounded, high-value use case — typically one that has a clear success metric, a finite set of input types, and a well-understood escalation path — and demonstrate measurable ROI within a 90-day engagement. From there, we work with clients to expand the agent's capability surface and integrate it with additional systems, building the governance and monitoring frameworks that allow it to operate at scale. Enterprise AI is not a technology challenge in isolation; it is a change management challenge, and we treat it as both.